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From a problem to its solution – learning computational thinking as a problem-solving skill as exemplified by England

Jan Bazyli Klakla

Living in society requires each of us to solve problems on a daily basis. The ability to deal with them, formulate them appropriately and then find solutions is one of the most important skills that we can acquire, and therefore should be one of the most important ones to be learned at school. Of course, there are many ways to solve problems. Moreover, many ways are effective and can lead us to the desired result. There are, however, ways that seem to increase in importance with technological change in the world.

One of them is computational thinking. I wrote more about computational thinking as a new skill for new times in my previous text. It is a way of solving problems, which is based on choosing the right abstractions and automation of those abstractions. Thus it allows reformulating complex problems into one which we know how to solve, using abstractions and decomposition.

From the perspective of the education system, as well as those who should be key in it, i.e. students, the mere statement that computational thinking is an important skill that should be taught in school does not say much. It is very important how it will be done. Education systems, like all systems, are resistant to change. Hence, it is not easy to find one that would boldly and comprehensively implement learning of computational thinking. However, there are some countries that are making attempts, and one of them is England.

The Royal Society’s definition of computational thinking highlights what I, too, emphasized in my previous text on this topic: that this way of solving problems is a human and humanistic way, not a machine and dehumanized one. It points out that approaches, tools, and techniques from computer science can help us understand and reason about both natural and artificial systems and processes in the world around us.

Hence, teaching computational thinking in England aims to equip students with specific “component skills,” the meaning of which is not limited to computer science: logical reasoning, modeling and abstraction. To use the words of Aman Yadav, professor at Michigan State University, what is important is the ability to be precise and to break down a problem into subproblems and develop solutions to subproblems and interactions between these solutions.

Thus, the English came from a simple but very important assumption that the convergent goal of both school education and computational thinking is the ability to solve problems. And because problems in today’s world are complex and diverse, solutions, and those who work on them, must be creative, not re-creative. And while creativity is something that each of us is born with as a human being, the development of this trait then depends on many factors, including what such a person will encounter during their education process.

Therefore, as of September 2014, they introduced a new compulsory curriculum for computing for 5–16 year-olds. It consists of four basic goals. The student should be able to:

1.     Understand and apply the fundamental principles and concepts of computer science, including abstraction, logic, algorithms, and data representation

2.     Analyze problems in computational terms and have repeated practical experience writing computer programs in order to solve such problems

3.     Evaluate and apply information technology, including new or unfamiliar technologies, analytically to solve problems

4.     Act as responsible, competent, confident, and creative users of information and  communication technology

Of course, this education covers many issues in the field of computer science. However, as I have already mentioned, the most interesting elements are those that are more universal in nature. And there are a lot of those in the English approach to learning computational thinking. Children aged 5-7 already learn what logical reasoning (in terms of cause/ effect) is. Moreover, they learn the advantage of this approach over simply guessing, as well as that there are many algorithms to solve real-world problems and that the choice of a good algorithm is the key to successfully solving a given problem. Slightly older students, aged 7-11, learn the structure of computational thinking in order to be able to design, use, and evaluate computational abstractions in the third stage, aged 12-14, that model the state and behavior of real-world problems.

After completing the initial stage of education, in their teens, English students are prepared to choose the path of their further adventure with computational thinking. They can devote themselves to computer science and related sciences, improving this skill at the academic and higher level. They can also choose a career and life path that is not directly related to programming. In the latter case, they still possess valuable problem-solving skills that they can use in their daily life.

Jan Bazyli Klakla

Recommended sources:

Department for Education. (2013). National curriculum in England: Computing programmes of study. Statutory Guidelines, 11 September 2013,

Naace & CAS. (2014). Joint guidance 2014. National curriculum for computing,

Yadav, Aman, et al. “Computational thinking as an emerging competence domain.” Competence-based vocational and professional education. Springer, Cham, 2017. 1051-1067.

About the author
Jan Bazyli Klakla
Having obtained a Master’s degree in both law and sociology, along with a Bachelor’s at the Centre for Comparative Studies of Civilisations (all three degrees at the Jagiellonian University in Kraków), he then received a postgraduate degree in international migration from the University of Warsaw. Currently, he is pursuing double Ph.D. in law and sociology at the Jagiellonian University. Simultaneously, he manages a research project on the impact of institutional and legal factors on the choice of acculturation strategies among foreigners in Poland.
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